The standard error of the fits (SE of fits) estimates the variation in the estimated mean response for a specified set of predictor values, factor levels, or components and is used to generate the confidence interval for the prediction. The smaller the standard error, the more precise the estimated mean response.
For example, your delivery time regression model predicts that a specific combination of predictor values (priority shipping, medium box, 500 miles) yields a predicted (fitted) mean delivery time of 3.80 days and an standard error of the fit of 0.08 days.
In conjunction with the fitted value, the standard error of the fit can be used to create a confidence interval for the predicted mean response for this combination of predictor settings. For instance, depending on your sample size, a prediction interval with 95% confidence will extend approximately +/- two standard error of the fits out from your predicted mean. For the example of the delivery time regression model, the 95% confidence interval for the predicted mean response is (3.64, 3.96) days. You can be 95% confident that the population mean falls within this range.