A type II error occurs when a null hypothesis that is actually false is incorrectly accepted as true. It represents failing to detect something that is present, like missing a wolf that is actually there. The probability of committing a type II error is represented by beta, and lower beta means higher statistical power to correctly reject a false null hypothesis.