High-dimensional spaces refer to mathematical spaces with a large number of dimensions, often used in fields like machine learning and data analysis to represent complex data structures. These spaces pose unique challenges such as the 'curse of dimensionality,' which can lead to increased computational complexity and data sparsity, affecting the performance of algorithms.