The Monte Carlo Fallacy, also known as the gambler's fallacy, is the mistaken belief that past random events can influence future outcomes in a random process. For example, if a coin is flipped and lands on heads several times in a row, someone might wrongly assume that tails is "due" to occur next, despite each flip being independent. This fallacy often occurs in gambling scenarios, where players may believe that a streak of losses or wins will affect future bets. Understanding that each event is independent helps individuals make more informed decisions and avoid the pitfalls of this cognitive bias.