As the title states, what exactly in Elasticsearch's fuzzy-query is related to fuzzy logic?

For example, given a string, a fuzzy query with fuzziness of 2 will return all indexed strings that have a Levenshtein distance of 2. How does the system decide what answers to return if there are multiple matches?

Is there a fuzzy system behind it? one that has triangular functions (for instance) and can be expressed in something like this:

```
1| A B
| /\ /\ A = fuzzy set 1
| / \/ \ B = fuzzy set 2
| / /\ \
0|/ / \ \
------------
a b c d
```

I would like a more theoretical answer that tackles what exactly in fuzzy queries is so fuzzy?