My question is, how do I interpret this? Does this mean that my data is normally distributed but has a non-zero mean (i.e. not standard normal) or does this probability only reflect something else?
You are correct. If you run normplot and get data very close to the fitted line, that means your data has a cumulative distribution function that is very close to a normal distribution. The 0.5 CDF point corresponds to the mean value of the fitted normal distribution. (Looks like about 0.002 in your case)
The reason you get a straight line is that the y-axis is nonlinear, and it's made to be "warped" in such a way that a perfect Gaussian cumulative distribution would map into a line: the y-axis marks are linear with the inverse error function.
When you look at the ends and they have steeper slopes than the fitted line, that means your distribution has shorter tails than a normal distribution, i.e. there are fewer outliers, perhaps due to some physical constraint that prevents excessive variation from the mean.