The closest contenders that I could find so far are yEnc (2%) and ASCII85 (25% overhead). There seem to be some issues around yEnc mainly around the fact that it uses an 8-bit character set. Which leads to another thought: is there a binary to text encoding based on the UTF-8 character set?
This really depends on the nature of the binary data, and the constraints that "text" places on your output.
First off, if your binary data is not compressed, try compressing before encoding. We can then assume that the distribution of 1/0 or individual bytes is more or less random.
Now: why do you need text? Typically, it's because the communication channel does not pass through all characters equally. e.g. you may require pure ASCII text, whose printable characters range from 0x20-0x7E. You have 95 characters to play with. Each character can theoretically encode log2(95) ~= 6.57 bits per character. It's easy to define a transform that comes pretty close.
But: what if you need a separator character? Now you only have 94 characters, etc. So the choice of an encoding really depends on your requirements.
To take an extremely stupid example: if your channel passes all 256 characters without issues, and you don't need any separators, then you can write a trivial transform that achieves 100% efficiency. :-) How to do so is left as an exercise for the reader.
UTF-8 is not a good transport for arbitrarily encoded binary data. It is able to transport values 0x01-0x7F with only 14% overhead. I'm not sure if 0x00 is legal; likely not. But anything above 0x80 expands to multiple bytes in UTF-8. I'd treat UTF-8 as a constrained channel that passes 0x01-0x7F, or 126 unique characters. If you don't need delimeters then you can transmit 6.98 bits per character.
A general solution to this problem: assume an alphabet of N characters whose binary encodings are 0 to N-1. (If the encodings are not as assumed, then use a lookup table to translate between our intermediate 0..N-1 representation and what you actually send and receive.)
Assume 95 characters in the alphabet. Now: some of these symbols will represent 6 bits, and some will represent 7 bits. If we have A 6-bit symbols and B 7-bit symbols, then:
A+B=95 (total number of symbols) 2A+B=128 (total number of 7-bit prefixes that can be made. You can start 2 prefixes with a 6-bit symbol, or one with a 7-bit symbol.)
Solving the system, you get: A=33, B=62. You now build a table of symbols:
Raw Encoded 000000 0000000 000001 0000001 ... 100000 0100000 1000010 0100001 1000011 0100010 ... 1111110 1011101 1111111 1011110
To encode, first shift off 6 bits of input. If those six bits are greater or equal to 100001 then shift another bit. Then look up the corresponding 7-bit output code, translate to fit in the output space and send. You will be shifting 6 or 7 bits of input each iteration.
To decode, accept a byte and translate to raw output code. If the raw code is less than 0100001 then shift the corresponding 6 bits onto your output. Otherwise shift the corresponding 7 bits onto your output. You will be generating 6-7 bits of output each iteration.
For uniformly distributed data I think this is optimal. If you know that you have more zeros than ones in your source, then you might want to map the 7-bit codes to the start of the space so that it is more likely that you can use a 7-bit code.