High-dimensional data refers to datasets with a large number of variables or features, often leading to challenges in analysis due to the 'curse of dimensionality'. This complexity can result in overfitting, increased computational cost, and difficulties in visualization and interpretation, necessitating advanced techniques for effective analysis.