The Noisy Channel Model is a framework used in information theory and computational linguistics to understand and correct errors in message transmission over a channel that introduces noise. It is fundamental in developing algorithms for tasks like speech recognition, spelling correction, and machine translation by leveraging probabilistic models to infer the most likely intended message.