What is a major challenge when using high-dimensional datasets in machine learning (ML)?

It increases computational costs and complexity

Explanation

High-dimensional data can lead to increased processing time, memory usage, and model overfitting, making  it harder to extract meaningful insights.  more dimensions often require additional tuning to prevent overfitting, and they typically make interpretation more difficult, not easier.  More features do not always lead to higher accuracy.