Specifically, if for each tag we simply assume one count for each entry in the tag dictionary and one count for unknowns and then normalize, the probability of an unknown word having a specific tag is inversely correlated with the number of word types associated with the tag in the tag dictionary.
a tag that appears with a smaller number of distinct words will be seen by the HMM as being a better candidate tag for an unknown word.