Yes, that’s a good scenario.
The reason to use outlier rejection is to remove things that are well outside the normal statistical variation.
So, if you have a waterfall, each pixel in the waterfall will be some shade of blue to white, in a statistical distribution. The final averaged picture will be the average tone.
If a brightly colored bird flies in front of the waterfall briefly, those pixels should be outliers in the same way that a satellite or airplane track is for astro photos. The outlier rejection should find and toss them.