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The Curse of Dimensionality refers to the challenges and limitations associated with high-dimensional data, such as increased computational complexity, sparsity of data, and difficulty in visualization. It is relevant to unsupervised learning algorithms like PCA and t-SNE, which aim to reduce the dimensionality of data.