Multidimensional Scaling (MDS) is a statistical technique used for visualizing the level of similarity or dissimilarity of data in a low-dimensional space, often for exploratory data analysis. It transforms high-dimensional data into a spatial representation, where the distances between points reflect the original pairwise dissimilarities as closely as possible.