The Viterbi algorithm is a dynamic programming algorithm designed to find the most likely sequence of hidden states that would explain a given sequence of observed events, particularly within Hidden Markov Models (HMMs). Named after Andrew Viterbi, who proposed it in 1967 for decoding convolutional codes in noisy digital communication, it's notable for having been independently discovered by several researchers. This powerful algorithm is universally applied in diverse fields, from decoding digital cellular and satellite communications (CDMA, GSM, 802.11 Wi-Fi) to crucial tasks in speech recognition and bioinformatics. For instance, in speech-to-text, it determines the most probable string of words from an acoustic signal. The result, often called the "Viterbi path," represents this optimal sequence. Today, the Viterbi algorithm and path are standard terms for using dynamic programming to solve probability maximization problems in areas like statistical parsing and target tracking.