Update device-selection-explainer.md

This commit comprehensively updates the device selection explainer to reflect the latest discussions, API changes, and community feedback.

Key changes include:
- Updated Introduction and History sections to accurately reflect the removal of `MLDeviceType` from `MLContextOptions` (following PR webmachinelearning#809) and the shift towards hint-based, implementation-led device selection.
- Clarified the impact of key issues (webmachinelearning#749, webmachinelearning#302, webmachinelearning#350) and PRs (webmachinelearning#809, webmachinelearning#824, webmachinelearning#855) on the device selection strategy.
- Ensured the "Key use cases and requirements" section aligns with the current API, incorporating the device preference use cases from PR webmachinelearning#855.
- Updated JavaScript examples in "Scenarios, examples, design discussion" to be consistent with the current API, marking future/hypothetical features (like `opSupportLimitsPerDevice()` and a `fallback` option) with explanatory notes.
- Added new open questions based on recent discussions (e.g., issue webmachinelearning#836, PR webmachinelearning#854 regarding querying actual device usage).
- Refined the "Background thoughts" section, particularly the "Example Hardware Selection Guide," adding an editor's note about ongoing discussions (PR webmachinelearning#860).
- Corrected the "Considered alternatives" and "Minimum Viable Solution" sections to accurately represent the current and past approaches.
- Updated the "Next Phase Device Selection Solution" to clarify the status of proposals like `querySupport` (issue webmachinelearning#815) and the investigation of `graph.devices` (issue webmachinelearning#836, PR webmachinelearning#854).
- Performed a full proofread, correcting grammar, typos, and markdown formatting for improved clarity and consistency throughout the document.

Author: google-labs-jules[bot]