https://en.wikipedia.org/wiki/Aliasing
Even analog imaging has concerns that are better described in the frequency domain than the spatial domain:
The difference is audio is "actually" bandlimited and frequency-based, but images are "actually" spatial. When you try using frequency math on images you get artifacts called ringing, which are easy to see with JPEGs or sharp scalers like Lanczos.
Of course audio isn't really frequency-based either, or else it would just be one sound repeated forever. So there's still ringing artifacts (called "pre-echo") and cymbals are the first to go in an MP3.
I.e. audio is sampled along one dimension, while images are sampled along two dimensions. Note that frequency-domain considerations play a crucial role in all optical design, including imaging sensors.
For the mathematically inclined, this would probably be a good time to repeat: pixels are not little squares[1].
Early low data rate codecs - such as the one used for GSM mobiles - are obviously inferior, but still functional. I think a better analogy is that an iPhone 7 has a 1 megapixel screen, so there's no difference between a 1 megapixel image and a 5 megapixel image, except one is much larger. Of course visually you can zoom in (or move closer in real life), but audibly you can't.
Another way to look at is that digital audio is not like digital imaging. There aren't pixels. Increasing the data rate does not continue to make the waveform more and more detailed to human auditory perception in the way that raising the pixel density does for human visual perception.
To describe it intuitively, forget your intuition that audio is like visual and start from "there is no metaphor between these two things."