The normal plot is clearer. It shows the observations on the X axis plotted against the expected normal score (Z-score) on the Y axis. It’s not necessary to understand what an expected normal score is, nor how it’s calculated, to interpret the plot. All you need to do is check is that the points roughly follow the red-line. The red-line shows the ideal normal distribution with mean and standard-deviation of the sample. If the points roughly follow the line – as they do in this case – the sample has normal distribution.
And that’s the real beauty of the normal plot compared to the histogram – it's very easy to interpret. Visually, the human eye can better judge the points against a straight-line. And, unlike the histogram, there’s less ambiguity. You don’t have to try judge histogram bar-heights against the normal overlay curve.