A Naïve Bayes classifier is a probabilistic machine learning algorithm that is based on
Bayes' theorem and assumes independence between the features (hence the term 'naïve'). It is
widely used for classification tasks, particularly in natural language processing, text
classification, and spam filtering. The Naïve Bayes classifier calculates the probability of a given
instance belonging to a particular class based on the probabilities of its features. It assumes
that the presence or absence of each feature is independent of the presence or absence of
other features, which simplifies the calculations.