Is there a metaphor in machine learning for the following concept?

Given a list of ideas, which also has some “pseudo-notation” that may be more harmful than helpful, but I think is helping me:

• I would like to understand something meaningful about Y.
• Y seems to me to be dependent upon something about it’s relationship with an unknown, labeled X.
  • Y|~X
  • “Y given unknown entity X”
• I know that I do not know what X is.
  • How do I know that I don’t know what X is?
  • How do I know that I sense that Y seems to be in relationship with X?
  • How does knowing that I don’t understand the relation between Y and X factor into my current understanding of Y?
    • Y => Y(Y|~X)
• Given the existence of X, it seems likely that Y could also depend upon a relationship with Q, a thing I do not sense.
• Is there a way to incorporate my understanding of what I do not understand about Y=>X into my understanding of what I do not understand Q ?
  • Y => Y{(Y|~X), (Y|~[!Q||Q])}

Do we have a term for this? Here’s what I originally told Siri to make a note of, edited for clarity and word correction. “When a human being is thinking about something they know, and they already know what they don’t know and if they’re really paying attention they are simultaneously attempting to understand how “knowing that I know what I don’t know” factors into their thinking about “the thing they know”, and, they are also attempting to take into account that there are also things that they don’t even know that they don’t know. Does machine learning do anything like that?”