# How can Naive Bayes overfit the data?

I know that Laplace smoothing results in a high bias of Naive Bayes. If the value of the smoothing parameter (alpha) is large, then the probability distribution will be uniform for all the features. And Naive Bayes classifies based on the values of the likelihood of conditional probabilities. So the model will now classify based on the class label resulting in a high bias. Now, my question is can a Naive Bayes model overfit the data? If so How?