According to Wikipedia page on Naive Bayes:
.. Naive Bayes classifiers are a family of simple "probabilistic classifiers" based on applying Bayes' theorem with strong (naive) independence assumptions between the features.
Since data features may not be independent of each other, should one always perform PCA before applying Naive Bayes? PCA is expected to create components which are not much correlated with each other and hence one can expect more robust results with Naive Bayes.