This isn't learning by any means - this is just similarity. Machines don't understand what the words mean, nor the nuance of how to use them via this method.
Wiktionary terms "understand" as (i) be aware of the meaning of something (so we've just reduced it to the meaning of awareness and meaning), or (ii) to impute meaning that is not explicitly stated.
To put it in more colorful terms, a blind person can understand the difference between green, yellow and brown bananas, but they usually cannot understand the visual aspect of color.
By the same rationale, a vector does not understand the word it describes any more than the telephone book understands the people listed in it or the city that they live in.
Once you start to try to define aspects of cognition explicitly, things very quickly get ambiguous. Also, these conversations usually go along the lines of:
1. State a definition.
2. See that computer matches.
3. Decide it's wrong after all and try to change it so that computer can't match it.
4. Repeat until we find a definition that excludes computer.
I think it's a fascinating topic, but the above pattern is fairly disappointing.
That may be all that "learning" and "understanding" are.