The Viterbi Algorithm is a dynamic programming technique used to find the most likely sequence of hidden states in a Markov model. It is particularly useful in applications like speech recognition, bioinformatics, and error correction in communication systems. The algorithm works by breaking down the problem into smaller, manageable parts, calculating the probabilities of each state, and then selecting the best path through the states. By using a systematic approach, the Viterbi Algorithm efficiently traces back through the calculated probabilities to determine the optimal sequence. This makes it a powerful tool for decoding sequences where the underlying states are not directly observable, allowing for better predictions and interpretations of complex data.