What is the curse of dimensionality?

The curse of dimensionality refers to the challenges that arise when working with high-dimensional data. As the number of features (dimensions) increases:
The volume of the data space grows exponentially.
The data becomes sparse, making it harder to find meaningful patterns. This can result in overfitting and poor model performance, particularly in distance-based models like k-NN.