A fault that occurs during traditional hypothesis-based testing.
It occurs when the null hypothesis is rejected -- even though the null hypothesis is accurate and should not be rejected.
This error can be thought of more simply as a "false positive".
In other words, you incorrectly you declare a test a winner -- even though there's not actually a statistically significant difference between versions.
A type I error is the opposite of a type II error.