The Elbow method is a heuristic technique used in K-means clustering to determine the optimal number of clusters (K) by plotting the within-cluster sum of squares (WSS) against varying K values and identifying the "elbow" point where the rate of WSS decrease sharply bends, indicating diminishing returns for additional clusters.