Multi-dimensional Scaling (MDS) is a statistical technique used to visualize the level of similarity or dissimilarity of data in a low-dimensional space, often for the purpose of identifying patterns or clusters. It translates complex, high-dimensional data into a two or three-dimensional representation, preserving the relative distances between data points as much as possible.