The Naive Bayes Classifier is a classification model that uses Maximum a Posteriori to find the most probable class given a set o features, but the likelihood is simplified under the 'naive' assumption that, given any class, the features are mutually independent (which may in fact not be the case). Despite this assumption, the classifier works well in some applications, such as spam filtering.