Minkowski Distance is a mathematical metric used to measure the distance between two points in a space. It generalizes the concepts of both Euclidean Distance and Manhattan Distance. The formula involves taking the p-th root of the sum of the absolute differences raised to the power of p, where p can be any positive integer. For p=2, it becomes Euclidean Distance, and for p=1, it becomes Manhattan Distance. This distance metric is particularly useful in various fields such as machine learning, data analysis, and statistics. By adjusting the value of p, users can tailor the distance calculation to fit specific applications, allowing for greater flexibility in analyzing data patterns and relationships.