Word vectors like this only work if the two words you care about appear in similar contexts in the corpus it was trained on.
So the assumption is that words from similar context should be similar. But you're always going to miss out on some words that are similar but do not appear in similar contexts.
If the words are really similar in meaning, you should still be able to arrive at a useful result using some graph manipulations.
The words might not appear in a directly shared context, but given their semantic similarity, they should share more contexts of distance 1 (or something along those lines) than an arbitrary pair of words.
So the assumption is that words from similar context should be similar. But you're always going to miss out on some words that are similar but do not appear in similar contexts.