Hey there! Today we are going to explore an exciting topic in machine learning called Naive Bayes. By the end of this lesson, you'll understand what Naive Bayes is and how to implement it using Python's Scikit-Learn library. Let’s dive in!

Naive Bayes is a classification algorithm based on Bayes' Theorem. Imagine you’re a detective using clues (features) to decide who the culprit is (class). Naive Bayes helps by calculating probabilities.

Bayes' Theorem is stated as:

$P(C|X) = \frac{P(X|C) \cdot P(C)}{P(X)}$