Local Structure Preservation refers to the practice of maintaining the intrinsic geometric or topological properties of data when it is transformed or embedded into a different space. This is crucial in fields like dimensionality reduction and manifold learning, where preserving local relationships ensures that the essential characteristics and patterns of the data are retained and accurately represented in the new space.