Bayes theorem is more often about "how" than about "why".
"How" uses algebra as medium but does not give a clue about the actual aim.
"Why" refers to the target : adjusting risks (probabilities) to actual hazards; it's like drawing only what you have before your eyes. Conditional probabilities are easy to represent with algebraic symbols but very difficult to represent as physical entities (for our brains).
To understand the above picture, one may start from a vague prior idea of what the girl is doing, but intuitively we have to take into account what we actually see : cat's paws had to be cleaned.
Clearly, you have a higher risk of dying from elephant hazards than being eaten by a shark.
These worldwide statistics are true, but not useful. One needs to adjust risks to actual life hazards.
See also "posterior probabilities"
Looking for dung where the cow never browsed,
One possibility is just chance.
Paul Klee
After all it is not said that all things can be explained mathematically.