Understanding Type I Error in Hypothesis Testing

A manufacturing company wants to determine whether a new production method leads to fewer defects compared to their current production method. The null hypothesis ($H_0$) is that the new method does not reduce defects, while the alternative hypothesis ($H_1$) is that the new method does reduce defects.

In this context, a Type I error occurs if the company rejects the null hypothesis when it is actually true, meaning they conclude that the new method is better when it is not. A Type II error occurs if the company fails to reject the null hypothesis when it is false, implying they miss the opportunity to recognize that the new method is indeed better.

Which of the following statements accurately describes a Type I error in this scenario?