To answer my own question, the following example code shows how to add words to the embedding vocabulary. This requires a new embedding object to be created.
>> emb = fastTextWordEmbedding;
>> vocab = emb.Vocabulary;
>> mat = word2vec(emb, vocab);
>> newvocab = [vocab "New Word 1" "New Word 2"];
>> newmat = [mat; randn(2,300)];
>> newemb = wordEmbedding(newvocab, newmat);
In addition, I have confirmed it is possible to use the fastText pretrained 2 Million words (600 billion tokens) rather than the default 1 Million words (16 billion token) which is provided with the MATLAB fastTextWordEmbedding function.
To do this, replace the "wiki-news-300d-1M.vec.zip" file with the alternative pre-trained word vectors file from https://fasttext.cc/docs/en/english-vectors.html