As pointed out by the original proposers, one of the main advantages of these models is that the distributed representation achieves a level of generalization that is not possible with classical n-gram language models; whereas a n-gram model works in terms of discrete units that have no inherent relationship to one another, a continuous space model works in terms of word vectors where similar words are likely to have similar vectors.
when the model parameters are adjusted in response to a particular word or word-sequence, the improvements will carry over to occurrences of similar words and sequences.